Empirical studies of software defects rely on links between bug databases and program code repositories. This linkage is typically based on bug-fixes identified in developer-enter...
Adrian Bachmann, Christian Bird, Foyzur Rahman, Pr...
Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a g...
Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin ...
Under the homoscedastic Gaussian assumption, it has been shown that Fisher’s linear discriminant analysis (FLDA) suffers from the class separation problem when the dimensionalit...
The class of dual φ-divergence estimators (introduced in Broniatowski and Keziou (2009) [6]) is explored with respect to robustness through the influence function approach. For ...
Abstract. Empirical hardness models are a recent approach for studying NP-hard problems. They predict the runtime of an instance using efficiently computable features. Previous res...